Engineering Manager

This role is for one of the Weekday's clients

Salary range: Rs 5000000 - Rs 8000000 (ie INR 50-80 LPA)

Experience: 12+ yrs

Location: Bengaluru

Job Type: full-time

We are seeking an experienced Engineering Manager to lead high-performing engineering teams responsible for building scalable enterprise platforms, intelligent automation solutions, and next-generation AI-powered products. This role is ideal for a technology leader with deep expertise in Java, Spring Boot, distributed systems, and emerging Agentic AI technologies who is passionate about driving engineering excellence while delivering impactful business outcomes.

As an Engineering Manager, you will be responsible for leading multiple engineering initiatives, defining technical strategy, mentoring engineering teams, and ensuring the successful delivery of highly scalable and reliable software solutions. You will work closely with product managers, architects, data scientists, AI specialists, and senior business stakeholders to transform complex requirements into innovative technology solutions.

A significant aspect of this role involves driving the adoption of Agentic AI frameworks and Large Language Model (LLM)-powered systems to enhance automation, productivity, customer experiences, and business operations. You will help shape the organization's AI engineering roadmap while ensuring that solutions remain scalable, secure, maintainable, and aligned with business objectives.

The ideal candidate combines strong technical depth with leadership capabilities and possesses a proven track record of managing engineering teams, scaling platforms, and delivering mission-critical applications in fast-paced environments.

Requirements

Key Responsibilities

Engineering Leadership & Team Management

• Lead, mentor, and develop high-performing software engineering teams.
• Foster a culture of innovation, accountability, collaboration, and continuous learning.
• Drive engineering excellence through code reviews, technical mentorship, and best practices.
• Support career development, performance management, and succession planning for engineering talent.
• Create an environment that promotes ownership, quality, and operational excellence.

Architecture & Technical Strategy

• Define and execute technical roadmaps aligned with product and business goals.
• Architect and oversee the development of scalable applications using Java, Spring Boot, microservices, and distributed system principles.
• Establish engineering standards, design patterns, and architectural guidelines across teams.
• Drive platform modernization initiatives and continuous improvement efforts.
• Ensure systems are designed for scalability, resilience, security, and maintainability.

Agentic AI & Intelligent Systems

• Lead the development and implementation of Agentic AI-powered applications and workflows.
• Drive adoption of AI agents, intelligent automation, orchestration frameworks, and autonomous decision-making systems.
• Collaborate with AI and data teams to integrate LLM-powered capabilities into enterprise products.
• Evaluate emerging AI technologies and identify opportunities to create business value through automation and intelligence.
• Establish governance, reliability, and monitoring standards for AI-enabled systems.

Product Delivery & Execution

• Partner with product management and stakeholders to prioritize initiatives and define execution strategies.
• Manage project planning, resource allocation, risk mitigation, and delivery timelines.
• Ensure timely delivery of high-quality software through Agile development methodologies.
• Monitor project health, team velocity, and engineering performance metrics.
• Remove delivery bottlenecks and enable teams to achieve business objectives efficiently.

Engineering Operations & Platform Excellence

• Drive adoption of CI/CD pipelines, DevOps practices, automated testing, and release management processes.
• Promote observability, monitoring, performance optimization, and operational readiness.
• Ensure engineering teams follow security, compliance, and quality standards.
• Support cloud-native architectures and modern software deployment practices.
• Drive initiatives focused on reducing technical debt and improving platform reliability.

What Makes You a Great Fit

• 12+ years of software engineering experience, including significant leadership and people management responsibilities.
• Strong hands-on expertise in Java, Spring Boot, enterprise application development, and distributed systems.
• Proven experience managing engineering teams and delivering large-scale software platforms.
• Deep understanding of microservices architecture, REST APIs, event-driven systems, and cloud-native development.
• Experience building highly scalable, resilient, and performance-oriented applications.
• Strong knowledge of Agentic AI concepts, intelligent automation frameworks, and AI-driven product development.
• Exposure to Large Language Models (LLMs), prompt engineering, AI orchestration frameworks, RAG architectures, and AI application development.
• Experience integrating AI-powered solutions into enterprise workflows and customer-facing products.
• Strong understanding of software design principles, system architecture, and engineering best practices.
• Experience with Agile methodologies, DevOps practices, CI/CD pipelines, and engineering process optimization.
• Excellent stakeholder management, communication, and cross-functional collaboration skills.
• Proven ability to influence technical direction and align engineering initiatives with business goals.
• Strong analytical thinking and problem-solving capabilities.
• Passion for mentoring engineers and building high-performance engineering cultures.
• Ability to balance strategic leadership with hands-on technical decision-making.